Dynamic location accuracy deviation system

ABSTRACT

The present technology pertain to a continuous calibration performed by real-time location system controller to continuously calibrate itself to handle data received from network infrastructure devices more accurately, and to use this continuous calibration to accurately predict a location of a portable computing device.

TECHNICAL FIELD

The present technology pertains to identifying locations of wirelessdevices indoors, and more specifically pertains to repeatedly andautomatically calibrating a location controller to account for changesin a Wi-Fi environment.

BACKGROUND

Enterprise networks can track locations of wireless devices using radiofrequency location tracking techniques. Enterprises can use existingwireless infrastructure such as wireless access points, and sensors toreport measurements from which the location of a wireless device can beapproximated. Several techniques or combinations of techniques can beused including time of arrival, time difference of arrival, receivedsignal strength, and angle of arrival techniques.

The most common technique utilizes received signal strength (RSS)information. Access points, typically mounted on the ceiling, canreceive a signal from a wireless device, typically near ground level(desk surface, in a user's hand or pocket, etc.) and detects the averagesignal level of transmissions between the wireless device and eachaccess point. The signal level can be used to derive a distance fromeach access point. An indoor location controller can determine points inwhich the distances from two or more access points overlap and canthereby determine probable locations that the wireless device might belocated. The more access points that provide signal level datapertaining to that wireless device, the more accurately the probablelocation will match the true location.

While all of the techniques or combinations of techniques listed aboveperform well in the right circumstance, determining location indoors isa challenge for all of the techniques. Determining location indoors is achallenge due to the fact that the radio frequency environment isinfluenced by obstacles such as walls, and interference from other radiofrequency emitting devices and electronics in the environment.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to describe the manner in which the above-recited and otheradvantages and features of the disclosure can be obtained, a moreparticular description of the principles briefly described above will berendered by reference to specific embodiments thereof which areillustrated in the appended drawings. Understanding that these drawingsdepict only exemplary embodiments of the disclosure and are nottherefore to be considered to be limiting of its scope, the principlesherein are described and explained with additional specificity anddetail through the use of the accompanying drawings in which:

FIG. 1 illustrates an example system embodiment for carrying out thepresent technology;

FIG. 2 illustrates an example method performed by real-time locationsystem controller to continuously calibrate itself to handle datareceived from network infrastructure devices more accurately, and to usethis continuous calibration to accurately predict a location of aportable computing device;

FIG. 3 illustrates an example of a calculation of a location of anetwork infrastructure device in accordance with some aspects of thepresent technology; and

FIG. 4 illustrates an example computing system embodiment in accordancewith some aspects of the present technology.

DESCRIPTION OF EXAMPLE EMBODIMENTS

Various embodiments of the disclosure are discussed in detail below.While specific implementations are discussed, it should be understoodthat this is done for illustration purposes only. A person skilled inthe relevant art will recognize that other components and configurationsmay be used without parting from the spirit and scope of the disclosure.

Overview

The present technology pertains to continuous calibration by a real-timelocation system controller to handle data received from networkinfrastructure devices more accurately, and to use this continuouscalibration to accurately predict a location of a portable computingdevice.

In some embodiments, the present technology can periodically receivemeasurements, from at least two network-infrastructure devices. Themeasurements can be interpreted by a real-time location systemcontroller to derive a location of a first one of thenetwork-infrastructure devices. The respective measurements are relativeto a distance from the at least two of the network-infrastructuredevices to the first one of the plurality of network-infrastructuredevices. Based on the periodically received measurements, the real-timelocation system controller can repeatedly derive a calculated locationof the first of the network-infrastructure devices. The real-timelocation system controller can determine that the calculated location ofthe first one of the plurality of network-infrastructure devices isdifferent than the known location of the first one of the plurality ofnetwork-infrastructure devices, and apply at least one elasticitycoefficient to at least one measurement from at least two of theplurality of network-infrastructure devices from which the measurementswere received.

In some embodiments, a real-time location system controller can, at afirst time, receive measurements regarding a location of a firstnetwork-infrastructure device having a known location from a pluralityof other network-infrastructure devices each having a respective knownlocation. Using the measurements at the first time, the real-timelocation system controller can calculate a location of the firstnetwork-infrastructure device to yield a calculated location, at thefirst time, for the first network infrastructure device. The real-timelocation system controller can compare the calculated location of thefirst network-infrastructure device to the known location of the firstnetwork-infrastructure device, and determine a first discrepancy betweenthe calculated location of the first network-infrastructure device andthe known location of the first network-infrastructure device. Thereal-time location system controller can apply a first elasticitycoefficient to the measurements from at least one of the plurality ofother network-infrastructure devices that when applied to themeasurements received at the first time results in a determination thatthe first network-infrastructure device is located at the known locationfor the first network-infrastructure device.

EXAMPLE EMBODIMENTS

Additional features and advantages of the disclosure will be set forthin the description which follows, and in part will be obvious from thedescription, or can be learned by practice of the herein disclosedprinciples. The features and advantages of the disclosure can berealized and obtained by means of the instruments and combinationsparticularly pointed out in the appended claims. These and otherfeatures of the disclosure will become more fully apparent from thefollowing description and appended claims, or can be learned by thepractice of the principles set forth herein.

The disclosed technology addresses the need in the art for an improvedindoor location system using wireless infrastructure. As addressedabove, determining location indoors is a challenge due to the influenceof obstacles such as walls, and interference from other radio frequencyemitting devices and electronics in the environment. While some indoorlocation solutions attempt to overcome this challenge by takingmeasurements within the environment to determine average deviations fromtheoretical, expected values, and then apply a persistent adjustmentcoefficient to compensate for this average observed deviation, such asolution is not enough.

Even when using the persistent adjustment coefficient to compensate forthis average observed deviation, such a solution treats an average in anarea as applicable to all measurements from all devices, and from allplanes of measurement. The amount of compensation a particular accesspoint might need can be different the amount of compensation anotheraccess point might need. Even the amount of compensation a particularaccess point might need in one plane or direction can be different thatthe amount of compensation the particular access point might need inanother plane or direction—as might be the case if an access point has awall on one side. The present technology solves this problem bydetermining and applying different coefficients to locations derivedfrom data different access points, and to locations derived from datarecorded in one direction or plane compared to another direction orplane on the same access point.

The present technology also addresses the problem caused by the dynamicindoor radio frequency (RF) environment, such as a Wi-Fi environment. Aspeople move around the environment, or new walls are constructed, or newequipment is installed, the measurements from a particular access point,in a particular direction might change overtime. The present technologyalso solves this problem by continually determining the locations ofdevices for which location is already known to repeatedly recalibratethe various wireless-network-infrastructure devices.

FIG. 1 illustrates an example system embodiment for carrying out thepresent technology. FIG. 1 shows an example network for providingwireless (Wi-Fi) access to computing devices.

In some embodiments, the system illustrated in FIG. 1 represents aportion of an enterprise network that is administrated throughenterprise network controller 102. Enterprise network controller 102 canbe responsible for the set up and management of various network devicesand services. Enterprise network controller 102 can also be responsiblefor controlling access by users and devices. In general enterprisenetwork controller 102 can handle all functions related to themanagement of an enterprise network.

One aspect of an enterprise network is to provide connectivity to one ormore devices. FIG. 1 illustrates a plurality of network infrastructuredevices 106 such as network infrastructure device 106 ₁, 106 ₂, 106 ₃,and 106 _(n) representing any number of different infrastructuredevices. While an enterprise network may have other networkinfrastructure devices other than wireless network infrastructuredevices, FIG. 1 illustrates wireless network infrastructure devices 106.

In some embodiments, a wireless network infrastructure device 106 caninclude a wireless access point which can provide wireless access to oneor more client devices 108. In some embodiments, a wireless networkinfrastructure device 106 can include an active sensor, which can belocated in the enterprise environment and can receive signals emitted bywireless access points and other active sensors and can report back toenterprise network controller 102 regarding measurements that reflectthe performance of the wireless network or one or more wireless networkinfrastructure devices 106.

In some embodiments, network infrastructure devices 106 can beconfigured by enterprise network controller 102. Part of theconfiguration of network infrastructure devices 106 is to record alocation in the physical environment in which a particular networkinfrastructure device 106 is located.

FIG. 1 also illustrates real-time location system controller 104. Whilereal-time location system controller 104 is shown to be separate fromenterprise network controller 102 or from the network infrastructuredevices 106, real-time location system controller 104 can be integratedwith any other computing device on the enterprise network includingenterprise network controller 102 and network infrastructure devices106.

Real-time location system controller 104 can be used to determine alocation of one or more devices such as a network infrastructure device106 (whether an access point or an active sensor), or portable computingdevice 108. Real-time location system controller 104 can determine alocation of a wireless device using any of several techniques orcombinations thereof including: time of arrival, time difference ofarrival, received signal strength (RSS), and angle of arrival (AoA)techniques.

The most common technique utilizes received signal strength (RSS)information. Access points, typically mounted on the ceiling, receive asignal from a wireless device, typically near ground level (desksurface, in a user's hand or pocket, etc.) and detects the averagesignal level of transmissions between the wireless device and eachaccess point. The signal level can be used to derive a distance fromeach access point. An indoor location controller can determine points inwhich the distances from two or more access points overlap and probablelocations that the wireless device might be located. The more accesspoints that provide signal level data pertaining to that wirelessdevice, the more accurately the probable location will match the truelocation.

Another common technique is angle of arrival (AoA). This technique candetermine a direction or plane from which a communication wastransmitted by determining a direction in which an antenna is pointedthat receives the strongest average signal. When this is performed bytwo or more devices, each device can project an imaginary plane, and theintersection point between two or more planes is the likely location ofthe transmitting device.

In some embodiments, real-time location system controller 104 can alsobe used to calibrate itself to make more accurate location estimations.Real-time location system controller 104 can receive measurements madeby the various network infrastructure devices 106 that can be used tocalculate the location of one or more of the network infrastructuredevices 106. Since the location of each of the network infrastructuredevices 106 is known, real-time location system controller 104 candetermine that it is not calibrated for the current conditions presentin the Wi-Fi environment when it calculates that one of the networkinfrastructure devices 106 is not where it is known to be.

FIG. 2 illustrates an example method performed by real-time locationsystem controller 104 to continuously calibrate itself to handle datareceived from network infrastructure devices 106 more accurately, and touse this continuous calibration to accurately predict a location of aportable computing device 108.

Real-time location system controller 104 can receive measurements fromnetwork infrastructure devices 106. (The measurements can be averages ofa plurality of measurements taken over a short period.) Thesemeasurements can be received continuously, periodically, or at leastrepeatedly at a first time and repeated again at a second time as onegoal real-time location system controller 104 is to calibrate itself tothe current conditions of the enterprise Wi-Fi environment.

In some embodiments, the received (202) measurements from networkinfrastructure devices 106 can be measurements regarding a signalstrength of nearby network infrastructure devices. For example, asillustrated in FIG. 3, network infrastructure devices 106 ₁, 106 ₂, 106₃, and 106 ₄ can report on measurements of received signal strength ofnetwork infrastructure device 106 ₅.

Real-time location system controller 104 can use the receivedmeasurements to derive (204) a calculated location of one of theplurality of network infrastructure devices. As illustrated in FIG. 3,measurements received from network infrastructure devices 106 ₁, 106 ₂,106 ₃, and 106 ₄ can be used to calculate (204) the location 275 ofnetwork infrastructure device 106 ₅.

Real-time location system controller 104 can then determine (206)whether the calculated (204) location of the first one of the networkinfrastructure devices is different than the location that is known forthat network infrastructure device. As illustrated in FIG. 3, real-timelocation system controller 104 can determine (206) that the calculated(204) location 275 is different than the known location 279.

When real-time location system controller 104 determines (206) that thecalculated (204) location of the first one of the network infrastructuredevices is different than the location that is known for that networkinfrastructure device, real-time location system controller 104 cancalculate (208) at least one elasticity coefficient that when used tocalculate the location of the first one of the network infrastructuredevices results in a calculated location in three-dimensional space forthe first one of the network infrastructure devices that sufficientlycorresponds to the known location of the first one of the networkinfrastructure devices.

For example, FIG. 3 further shows a Riemanian space between networkinfrastructure devices 106 ₁, 106 ₂, 106 ₃, and 106 ₄ and the knownlocation of network infrastructure device 106 ₅. Real-time locationsystem controller 104 can calculate (208) how calculations made toderive (204) the calculated location 275 would need to be adjusted (acoefficient that can be included to make this adjustment is a elasticitycoefficient) to match the Riemanian space.

In some embodiments, real-time location system controller 104 candetermine that its original calculation (204) resulted in deriving acalculated location that was incorrect in one or more planes ordirections. In such embodiments, the elasticity coefficient might onlybe applied to calculations that rely on data measured in the plane ordirection in which the original calculation (204) was incorrect. In someembodiments, a different elasticity coefficient can be applied to eachdifferent direction or plane that relies on data measured in the planesor directions in which the original calculation (204) was incorrect.

An objective of performing steps 204, 206, 208 is to determine that anaspect of the Wi-Fi environment is different than expected. This can becaused by people walking around in the space covered by the Wi-Fienvironment, or physical changes in the space or interference or otherfactors. As such, the present technology utilizes the elasticitycoefficients to compensate for the aspect(s) of the Wi-Fi environmentthat is different than expected.

Accordingly, real-time location system controller 104 can apply (210)the at least one elasticity coefficient to a calculation to determinethe location of a portable computing device when the calculationutilizes data that is collected from one of the plurality of networkinfrastructure devices in a portion of the Wi-Fi environment for whichother measurements have needed compensation to account for aspects ofthe Wi-Fi environment that are different than expected.

As illustrated in FIG. 2, after real-time location system controller 104performs step 210 the method can return to step 202. However, a morerealistic description would be that the real-time location systemcontroller 104 can be continuously performing any of the stepsillustrated in FIG. 2, and the steps illustrated in FIG. 2 likely willbe executed in parallel operations that amount to a continuouscalibration of real-time location system controller 104 to the observedconditions of the Wi-Fi environment and continuous application of thecalibration through use of the calculated coefficients to determine nearreal time locations of portable computing devices in the Wi-Fienvironment.

As illustrated in FIG. 2, and in some embodiments, after real-timelocation system controller 104 has calculated (208) an elasticitycoefficient to compensate for observed conditions in the Wi-Fienvironment, future calculations (204) of the location of one of theplurality of network infrastructure devices may sufficiently correspondto the known location. This may repeatedly occur such that it can beassumed that the Wi-Fi environment includes a persistent change and thatthe elasticity coefficient should become a persistent part of thecalculation of locations of portable computing devices and that part ofthe Wi-Fi environment. This operation is reflected in steps 212, 214,and 216.

At step 212, real-time location system controller 104 can determine(212) whether the elasticity coefficient has previously been applied tocalculations for the location of one of the plurality of networkinfrastructure devices 106. When real-time location system controller104 determines (212) that the elasticity coefficient has previously beenapplied, it can further determine (214) whether the same orapproximately the same elasticity coefficient has been applied forgreater than a specified period of time, and if so the real-timelocation system controller 104 can replace (216) the persistentadjustment coefficient for one of the plurality of networkinfrastructure devices with a new persistent adjustment coefficient thatreflects adjustments made by the elasticity coefficient. In this way theeffect of the elasticity coefficient can become persistent.

While the above description may, for simplicity, refer to calculation ofone elasticity coefficient, it should be appreciated by those ofordinary skill in the art that in reality many elasticity coefficientsare calculated. A different elasticity coefficient may need to beapplied to calculations using data received from each different networkinfrastructure device 106. In other words, when determining the locationof infrastructure network infrastructure device 106 ₅ in FIG. 3, adifferent elasticity coefficient may need to be applied to calculationsregarding data from infrastructure device 106 ₁, and a differentelasticity coefficient may need to be applied to calculations regardingdata from infrastructure device 106 ₂, and from network infrastructuredevice 106 ₃, and from network infrastructure device 106 ₄.

In some embodiments, multiple elasticity coefficients need to beprovided to different measurements from the same network infrastructuredevice 106 when the measurements are in different planes or directionsand greater signal degradation exists in one of the planes or directionsthan another.

The present technology provides many benefits over the previousstate-of-the-art. For example, real-time location system controller 104can calibrate itself using network infrastructure devices 106. Whereasprior systems were manually calibrated and applied a single persistentadjustment coefficient to all calculations of device location.

Additionally, real-time location system controller 104 can dynamicallyand repeatedly calculate elasticity coefficients so that calculations oflocations of network infrastructure devices 106 and portable computingdevices 108 are more accurate since they compensate for current Wi-Fienvironment conditions.

Furthermore, the present technology calculates elasticity coefficientsin multiple plans. Since the present technology makes use of activesensors in the network infrastructure, which are typically located at ornear floor level, the present technology determines elasticitycoefficients for ceiling to floor planes (ceiling access points toactive sensors), ceiling to ceiling planes (ceiling access points toceiling access points), and floor to floor planes (active sensor toactive sensor). These measurements are combined iteratively to determinethe location accuracy deviation in each plane. It should be appreciatedthat active sensors can be mounted on walls or ceiling and access pointsare also not restricted to mounting on ceilings.

The overall result is that the present technology results in a systemthat is more accurate overall, and that is accurate in substantiallyreal time by accounting for dynamic changes in the Wi-Fi environment.

FIG. 4 shows an example of computing system 300, which can be forexample any computing device making up enterprise network controller102, real time location system controller 104, network infrastructuredevices 106 or any component thereof in which the components of thesystem are in communication with each other using connection 305.Connection 305 can be a physical connection via a bus, or a directconnection into processor 310, such as in a chipset architecture.Connection 305 can also be a virtual connection, networked connection,or logical connection.

In some embodiments, computing system 300 is a distributed system inwhich the functions described in this disclosure can be distributedwithin a datacenter, multiple datacenters, a peer network, etc. In someembodiments, one or more of the described system components representsmany such components each performing some or all of the function forwhich the component is described. In some embodiments, the componentscan be physical or virtual devices.

Example system 300 includes at least one processing unit (CPU orprocessor) 310 and connection 305 that couples various system componentsincluding system memory 315, such as read only memory (ROM) 320 andrandom access memory (RAM) 325 to processor 310. Computing system 300can include a cache of high-speed memory 312 connected directly with, inclose proximity to, or integrated as part of processor 310.

Processor 310 can include any general purpose processor and a hardwareservice or software service, such as services 332, 334, and 336 storedin storage device 330, configured to control processor 310 as well as aspecial-purpose processor where software instructions are incorporatedinto the actual processor design. Processor 310 may essentially be acompletely self-contained computing system, containing multiple cores orprocessors, a bus, memory controller, cache, etc. A multi-core processormay be symmetric or asymmetric.

To enable user interaction, computing system 300 includes an inputdevice 345, which can represent any number of input mechanisms, such asa microphone for speech, a touch-sensitive screen for gesture orgraphical input, keyboard, mouse, motion input, speech, etc. Computingsystem 300 can also include output device 335, which can be one or moreof a number of output mechanisms known to those of skill in the art. Insome instances, multimodal systems can enable a user to provide multipletypes of input/output to communicate with computing system 300.Computing system 300 can include communications interface 340, which cangenerally govern and manage the user input and system output. There isno restriction on operating on any particular hardware arrangement andtherefore the basic features here may easily be substituted for improvedhardware or firmware arrangements as they are developed.

Storage device 330 can be a non-volatile memory device and can be a harddisk or other types of computer readable media which can store data thatare accessible by a computer, such as magnetic cassettes, flash memorycards, solid state memory devices, digital versatile disks, cartridges,random access memories (RAMs), read only memory (ROM), and/or somecombination of these devices.

The storage device 330 can include software services, servers, services,etc., that when the code that defines such software is executed by theprocessor 310, it causes the system to perform a function. In someembodiments, a hardware service that performs a particular function caninclude the software component stored in a computer-readable medium inconnection with the necessary hardware components, such as processor310, connection 305, output device 335, etc., to carry out the function.

For clarity of explanation, in some instances the present technology maybe presented as including individual functional blocks includingfunctional blocks comprising devices, device components, steps orroutines in a method embodied in software, or combinations of hardwareand software.

Any of the steps, operations, functions, or processes described hereinmay be performed or implemented by a combination of hardware andsoftware services or services, alone or in combination with otherdevices. In some embodiments, a service can be software that resides inmemory of a client device and/or one or more servers of a contentmanagement system and perform one or more functions when a processorexecutes the software associated with the service. In some embodiments,a service is a program, or a collection of programs that carry out aspecific function. In some embodiments, a service can be considered aserver. The memory can be a non-transitory computer-readable medium.

In some embodiments, the computer-readable storage devices, mediums, andmemories can include a cable or wireless signal containing a bit streamand the like. However, when mentioned, non-transitory computer-readablestorage media expressly exclude media such as energy, carrier signals,electromagnetic waves, and signals per se.

Methods according to the above-described examples can be implementedusing computer-executable instructions that are stored or otherwiseavailable from computer readable media. Such instructions can comprise,for example, instructions and data which cause or otherwise configure ageneral purpose computer, special purpose computer, or special purposeprocessing device to perform a certain function or group of functions.Portions of computer resources used can be accessible over a network.The computer executable instructions may be, for example, binaries,intermediate format instructions such as assembly language, firmware, orsource code. Examples of computer-readable media that may be used tostore instructions, information used, and/or information created duringmethods according to described examples include magnetic or opticaldisks, solid state memory devices, flash memory, USB devices providedwith non-volatile memory, networked storage devices, and so on.

Devices implementing methods according to these disclosures can comprisehardware, firmware and/or software, and can take any of a variety ofform factors. Typical examples of such form factors include servers,laptops, smart phones, small form factor personal computers, personaldigital assistants, and so on. Functionality described herein also canbe embodied in peripherals or add-in cards. Such functionality can alsobe implemented on a circuit board among different chips or differentprocesses executing in a single device, by way of further example.

The instructions, media for conveying such instructions, computingresources for executing them, and other structures for supporting suchcomputing resources are means for providing the functions described inthese disclosures.

Although a variety of examples and other information was used to explainaspects within the scope of the appended claims, no limitation of theclaims should be implied based on particular features or arrangements insuch examples, as one of ordinary skill would be able to use theseexamples to derive a wide variety of implementations. Further andalthough some subject matter may have been described in languagespecific to examples of structural features and/or method steps, it isto be understood that the subject matter defined in the appended claimsis not necessarily limited to these described features or acts. Forexample, such functionality can be distributed differently or performedin components other than those identified herein. Rather, the describedfeatures and steps are disclosed as examples of components of systemsand methods within the scope of the appended claims.

The invention claimed is:
 1. A system comprising: a real-time locationsystem (RTLS) controller comprising at least one processor and a storagefor storing processor executable instructions; a plurality ofnetwork-infrastructure devices, wherein the RTLS controller storeslocation data in the storage identifying a known location of thenetwork-infrastructure devices; wherein the instructions stored in thestorage of the RTLS controller are effective to cause at least oneprocessor to: periodically receive a measurements, from at least two ofthe plurality of network-infrastructure devices, that can be interpretedto derive a location of a first one of the plurality ofnetwork-infrastructure devices, wherein respective measurements arerelative to a distance from the at least two of the plurality ofnetwork-infrastructure devices to the first one of the plurality ofnetwork-infrastructure devices; based on the periodically receivedmeasurements, repeatedly derive a calculated location of the first oneof the plurality of network-infrastructure devices; determine that thecalculated location of the first one of the plurality ofnetwork-infrastructure devices is different than the known location ofthe first one of the plurality of network-infrastructure devices; applyat least one elasticity coefficient to at least one measurement from atleast two of the plurality of network-infrastructure devices from whichthe measurements were received.
 2. The system of claim 1, wherein anapplication of the at least elasticity coefficient results in thecalculated location of the first one of the plurality ofnetwork-infrastructure devices to sufficiently correspond to the knownlocation of the first one of the plurality of network-infrastructuredevices.
 3. The system of claim 1, wherein the periodically receivedmeasurements and application of the at least one elasticity coefficientresults in a substantially real time compensation for a present radiofrequency (RF) interference.
 4. The system of claim 1, wherein theinstructions stored in the storage of the RTLS controller are effectiveto cause at least one processor to: calculate the at least oneelasticity coefficient that results in the calculated location in 3-Dspace of the first one of the plurality of network-infrastructuredevices to sufficiently correspond to the known location of the firstone of the plurality of network-infrastructure devices in the 3-D space.5. The system of claim 1, wherein the calculated location of the firstone of the plurality of network-infrastructure devices further utilizesa persistent adjustment coefficient which accounts for an average RFperformance in an environment in which the plurality ofnetwork-infrastructure devices are installed.
 6. The system of claim 5,wherein the instructions stored in the storage of the RTLS controllerare effective to cause at least one processor to: determine that the atleast one elasticity coefficient of an approximately constant value ispersistently needed for measurements from a specific one of theplurality of network-infrastructure devices in at least one direction ofmeasurement; and replace the persistent adjustment coefficient for thespecific one of the plurality of network-infrastructure devices in theat least one direction of measurement with an updated coefficient thattakes into account the at least one elasticity coefficient.
 7. Thesystem of claim 1, wherein the at least one elasticity coefficient isspecifically applied to future measurements from a specificnetwork-infrastructure device from the specific direction in which themeasurements were received.
 8. The system of claim 1, wherein theinstructions stored in the storage of the RTLS controller are effectiveto cause at least one processor to: calculate the location of a portablecomputing device using measurements from the at least two of theplurality of network-infrastructure devices and applying the at leastone elasticity coefficient.
 9. A method performed by a real-timelocation system (RTLS), the method comprising: periodically receivingmeasurements, from at least two of a plurality of network-infrastructuredevices, that can be interpreted to derive a location of a first one ofthe plurality of network-infrastructure devices, wherein the respectivemeasurements are relative to a distance from the at least two of theplurality of network-infrastructure devices to the first one of theplurality of network-infrastructure devices; based on the periodicallyreceived measurements, repeatedly deriving a calculated location of thefirst one of the plurality of network-infrastructure devices;determining that the calculated location of the first one of theplurality of network-infrastructure devices is different than a knownlocation of the first one of the plurality of network-infrastructuredevices; applying at least one elasticity coefficient to at least onemeasurement from at least two of the plurality of network-infrastructuredevices from which the measurements were received.
 10. The method ofclaim 9, wherein the calculated location of the first one of theplurality of network-infrastructure devices further utilizes apersistent adjustment coefficient which accounts for an average RFperformance in an environment in which the plurality ofnetwork-infrastructure devices are installed.
 11. The method of claim10, comprising: determining that the at least one elasticity coefficientof an approximately constant value is persistently needed formeasurements from a specific one of the plurality ofnetwork-infrastructure devices in at least one direction of measurement;and replace the persistent adjustment coefficient for the specific oneof the plurality of network-infrastructure devices in the at least onedirection of measurement with an updated coefficient that takes intoaccount the at least one elasticity coefficient.
 12. The method of claim9, comprising: calculating the location of a portable computing deviceusing measurements from the at least two of the plurality ofnetwork-infrastructure devices and applying the at least one elasticitycoefficient.